Techniques for selective channel processing and data retention in an implantable medical device

ABSTRACT

Methods and apparatus for storing data records associated with a medical monitoring event in a data structure. An implanted device obtains data and stores the data in the data record in a first data structure that is age-based. Before an oldest data record is lost, the oldest data record may be stored in a second data structure that is priority index-based. The priority index may be determined by a severity level and may be further determined by associated factors. The implanted device may organize, off-load, report, and/or display a plurality of data records based on an associated priority index. Additionally, the implanted device may select a subset or composite of physiologic channels from the available physiologic channels based on a selection criterion.

This patent application claims priority to U.S. Provisional ApplicationSer. No. 60/624,232 filed Nov. 2, 2004, which is incorporated herein byreference in its entirety.

FIELD OF THE INVENTION

The invention relates to techniques for selecting, storing and reportingdata associated with physiologic signals that may be further associatedwith a neurological event.

BACKGROUND OF THE INVENTION

Nervous system disorders affect millions of people, causing death and adegradation of life. Nervous system disorders include disorders of thecentral nervous system, peripheral nervous system, and mental health andpsychiatric disorders. Such disorders include, for example withoutlimitation, epilepsy, Parkinson's disease, essential tremor, dystonia,headache, and multiple sclerosis (MS). Additionally, nervous systemdisorders include mental health disorders and psychiatric disorderswhich also affect millions of individuals and include, but are notlimited to, anxiety (such as general anxiety disorder, panic disorder,phobias, post traumatic stress disorder (PTSD), and obsessive compulsivedisorder (OCD)), mood disorders (such as major depression, bipolardepression, and dysthymic disorder), sleep disorders (narcolepsy),obesity, and anorexia.

As an example, epilepsy is the most prevalent serious neurologicaldisease across all ages. Epilepsy is a group of neurological conditionsin which a person has or is predisposed to recurrent seizures. A seizureis a clinical manifestation resulting from excessive, hypersynchronous,abnormal electrical or neuronal activity in the brain. (A neurologicalevent is an activity that is indicative of a nervous system disorder. Aseizure is a type of a neurological event.) This electrical excitabilityof the brain may be likened to an intermittent electrical overload thatmanifests with sudden, recurrent, and transient changes of mentalfunction, sensations, perceptions, and/or involuntary body movement.Because the seizures are unpredictable, epilepsy affects a person'semployability, psychosocial life, and ability to operate vehicles orpower equipment. It is a disorder that occurs in all age groups,socioeconomic classes, cultures, and countries. In developed countries,the age-adjusted incidence of recurrent unprovoked seizures ranges from24/100,000 to 53/100,000 person-years and may be even higher indeveloping countries. In developed countries, age specific incidence ishighest during the first few months of life and again after age 70. Theage-adjusted prevalence of epilepsy is 5 to 8 per 1,000 (0.5% to 0.8%)in countries where statistics are available. In the United States alone,epilepsy and seizures affect 2.3 million Americans, with approximately181,000 new cases occurring each year. It is estimated that 10% ofAmericans will experience a seizure in their lifetimes, and 3% willdevelop epilepsy by age 75.

There are various approaches in treating nervous system disorders.Treatment therapies can include any number of possible modalities aloneor in combination including, for example, electrical stimulation,magnetic stimulation, drug infusion, and/or brain temperature control.Each of these treatment modalities can be operated using closed-loopfeedback control. Such closed-loop feedback control techniques receivefrom a monitoring element a neurological signal that carries informationabout a symptom or a condition or a nervous system disorder. Such aneurological signal can include, for example, electrical signals (suchas EEG, ECoG, and/or EKG), chemical signals, other biological signals(such as change in quantity of neurotransmitters), temperature signals,pressure signals (such as blood pressure, intracranial pressure orcardiac pressure), respiration signals, heart rate signals, pH-levelsignals, and peripheral nerve signals (cuff electrodes on a peripheralnerve). Monitoring elements can include, for example, recordingelectrodes or various types of sensors.

For example, U.S. Pat. No. 5,995,868 discloses a system for theprediction, rapid detection, warning, prevention, or control of changesin activity states in the brain of a patient. Use of such a closed-loopfeed back system for treatment of a nervous system disorder may providesignificant advantages in that treatment can be delivered before theonset of the symptoms of the nervous system disorder.

During the operation of a medical device system, the patient is likelyto experience multiple detections of the nervous system disorder. Forexample, in the case of seizures, the patient may have thousands ofseizures over the course of a time period, but only a few will havebehavioral manifestations. The other seizure episodes that don't exhibitbehavioral manifestations are considered sub-clinical or electrographicseizures. When the medical device system monitors for seizureoccurrences, however, the medical device system will detect many seizureevents although only some of these events will spread to other parts ofthe brain such that the patient will exhibit it (e.g., convulsions,unconsciousness, etc.).

In order to effectively provide treatment therapy, an implanted devicemay be required to record physiologic data that is related to thedisorder. However, an implanted device is typically limited by memorycapacity and by battery capacity. Thus, the implanted device is limitedin the amount of data that can be stored and reported.

An implanted device often stores physiologic data in a data structureand manages memory allocation for the data structure. However, thememory allocation management supported by the implanted device may havedeficiencies. For example, with a FIFO memory buffer if the amount ofcollected physiologic data exceeds the available memory space, theoldest physiologic data is lost regardless of the importance of the lostdata.

It is therefore desirable to selectively store physiologic data in alimited memory space of an implanted device. The implanted device canreport the most relevant data from the stored data so that the implanteddevice can be configured to provide efficacious treatment.

BRIEF SUMMARY

The following represents a simplified summary of some embodiments of theinvention in order to provide a basic understanding of various aspectsof the invention. This summary is not an extensive overview of theinvention nor is it intended to identify key or critical elements of theinvention or to delineate the scope of the invention. Its sole purposeis to present some embodiments of the invention in simplified form as aprelude to the more detailed description that is presented thereafter.

In accordance with an aspect of the invention, data records associatedwith a physiologic event, e.g., a neurological event, are stored inmemory that includes a first data structure and a second structure. Animplanted device obtains acquired data and stores a data recordassociated with the data in a selected data entry of the first datastructure (e.g., an age buffer such as circular buffer). Before an olderdata record in the first data structure is replaced (completely orpartially) with a new data record, the older data record may stored inthe second data structure if the associated priority index exceeds athreshold criterion (e.g., exceeds a predetermined threshold valueand/or is larger than a corresponding priority index of any data recordthat is currently stored in the second data structure). With anotherembodiment of the invention, the older data record may be stored in amin-max heap in accordance with the associated priority index.

In accordance with another aspect of the invention, the priority indexthat is associated with a data record may be determined by the severitylevel of a physiologic event and may be further determined by associatedfactors that may include associated physiologic events.

In accordance with another aspect of the invention, in response to aninstruction from a clinician, an implanted device organizes storedphysiologic data according to the associated priority index and reportsa predetermined number of data records that are deemed as having ahigher priority index than the other stored data records.

In accordance with another aspect of the invention, a subset or acomposite of physiologic channels is selected from the availablephysiologic channels based on a selection criterion.

The subset of physiologic channels may be processed and/or stored by animplanted device.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified schematic view of a thoracic cavity leadlessmedical device implanted in a patient that monitors cardiac andrespiratory parameters in accordance with an embodiment of theinvention.

FIG. 2 is a simplified block diagram of a core monitor as shown in FIG.1.

FIG. 3 is a graphical representation of the signals sensed by coremonitor as shown in FIG. 1 above.

FIG. 4 is a flow diagram showing operation of a core monitor as shown inFIG. 1 above.

FIG. 5 shows a first apparatus for collecting physiologic data that canbe retained in accordance with an embodiment of the invention;

FIG. 6 is a simplified schematic view of an alternative embodiment of athoracic and cranial leaded medical device implanted in a patient thatmonitors cardiac, respiratory and brain parameters in accordance with anembodiment of the invention.

FIG. 7 is a simplified block diagram of a full monitor as shown in FIG.6 above.

FIG. 8 is a flow diagram showing operation of a full monitor as shown inFIG. 6 above.

FIG. 9 is a simplified schematic view of another embodiment of acardiac, cranial and phrenic nerve leaded medical device implanted in apatient that monitors cardiac, respiratory and brain parameters andprovides brain, respiration, and cardiac treatment thereof in accordancewith an embodiment of the invention.

FIG. 10 is a simplified block diagram of a full monitor with brain,respiration and cardiac stimulation therapy as shown in FIG. 9 above.

FIG. 11 is a flow diagram showing operation of a full monitor withtherapy (including brain, respiration and/or cardiac stimulationtherapy) as shown in FIG. 9 above.

FIG. 12 shows apparatus that supports reporting neurological data inaccordance with an embodiment of the invention;

FIG. 13 is a schematic diagram of a system utilizing any of theabove-described embodiments and allowing remote monitoring anddiagnostic evaluation of at risk patients.

FIG. 14 is a schematic diagram of an alternative system utilizing any ofthe above-described embodiments and allowing remote monitoring anddiagnostic evaluation of at risk patients.

FIG. 15 shows a scenario for storing neurological data in accordancewith an embodiment of the invention;

FIG. 16 shows a data structure for storing neurological data inaccordance with an embodiment of the invention;

FIG. 17 shows a flow diagram for reporting neurological data inaccordance with an embodiment of the invention;

FIG. 18 shows an exemplary data entry that contains physiologic data andthat may be retained in memory of an implantable medical device;

FIG. 19 shows components of the exemplary data entry as shown in FIG.18; and

FIG. 20 shows the selection of channel data for retention in a datastructure.

DETAILED DESCRIPTION OF THE INVENTION

The following description discloses techniques for selecting, storingand reporting data associated with physiologic signals that may befurther associated with a neurological event. These techniques aresuitable for use within any implantable medical device system including,but not limited to, a core monitoring device, a full monitoring device,and/or a combination monitoring and treatment device (e.g., involvingbrain, respiration, and/or cardiac physiologic signals, discussedbelow). For example, a core monitor system may consist of ECG andrespiratory inputs, a full monitor system may consist of ECG,respiratory and EEG inputs, a monitor/treatment system may includebrain, cardiac inputs and phrenic nerve stimulation in variouscombinations.

In an embodiment, the invention is implemented within an implantableneurostimulator system, however, as already discussed, those skilled inthe art will appreciate that the techniques disclosed herein may beimplemented generally within any implantable medical device systemhaving monitoring capabilities of physiological conditions of thepatient including, but not limited to, implantable drug deliverysystems, implantable systems providing stimulation and drug delivery,pacemaker systems, defibrillator systems, cochlear implant systems, andimplantable diagnostic system for detecting bodily conditions, includingthose in organs like the brain and/or the heart. The implantable medicaldevice may provide therapeutic treatment to neural tissue in any numberof locations in the body including, for example, the brain (whichincludes the brain stem), the vagus nerve, the spinal cord, peripheralnerves, etc. The treatment therapies can include any number of possiblemodalities alone or in combination including, for example, electricalstimulation, magnetic stimulation, drug infusion, brain temperaturecontrol, and/or any combination thereof.

In addition, the invention may be embodied in various forms to analyzeand treat nervous system and other disorders, namely disorders of thecentral nervous system, peripheral nervous system, and mental health andpsychiatric disorders. Such disorders include, for example withoutlimitation, epilepsy, Sudden Unexpected Death in Epilepsy Patients(SUDEP), Parkinson's disease, essential tremor, dystonia, multiplesclerosis (MS), anxiety (such as general anxiety, panic, phobias, posttraumatic stress disorder (PTSD), and obsessive compulsive disorder(OCD)), mood disorders (such as major depression, bipolar depression,and dysthymic disorder), sleep disorders (narcolepsy), obesity,tinnitus, stroke, traumatic brain injury, Alzheimer's, and anorexia.

The physiologic signals that are selected, stored and reported inaccordance with various aspects of the invention may include any numberof sensed signals. Such physiological signals can include, for example,electrical signals (such as EEG, ECoG and/or EKG), chemical signals,biological signals (such as change in quantity of neurotransmitters),temperature signals, pressure signals (such as blood pressure,intracranial pressure or cardiac pressure), respiration signals, heartrate signals, pH-level signals, activity signals (e.g., detected by anaccelerometer), and/or peripheral nerve signals (cuff electrodes on aperipheral nerve). Such physiological signals may be recorded using oneor more monitoring elements such as monitoring electrodes or sensors.For example, U.S. Pat. No. 6,227,203 provides examples of various typesof sensors that may be used to detect a symptom or a condition or anervous system disorder and responsively generate a neurological signal.In addition, various types of physiologic activities may be sensingincluding, for example, brain, heart and/or respiration.

As discussed, the techniques disclosed herein are suitable for usewithin any implantable medical device system including, but not limitedto, a core monitoring device, a full monitoring device, and/or acombination monitoring and treatment device. Each of these medicaldevice implementations are discussed in further detail below. Ingeneral, however, each of these embodiments utilize one or moremonitoring elements that receive signals associated with thephysiological conditions being sensed, a memory component that containsmultiple data structures (for example, at least one that is age-basedand at least one other that is priority-based), and a processingcomponent (logic or software) that stores data records in the datastructures as disclosed herein (utilizing, for example, severity andpriority determinations for the data).

Core Monitor

In an embodiment, a Core Monitor device monitors cardiac (ECG) andrespiration signals and records these signals as discussed herein.Real-time analysis of the ECG signal evaluates rate disturbances (e.g.,bradycardia; tachycardia; asystole) as well as any indications ofcardiac ischemia (e.g., ST segment changes; T wave inversion, etc.).Real-time analysis of the respiration signal evaluates respirationdisturbances (e.g., respiration rate, minute ventilation, apnea,prolonged pauses, etc.). Abnormalities detected during real-timeanalysis may lead to an immediate patient alert, which can be audible(beeps, buzzers, tones, spoken voice, etc.), light, tactile, or othermeans. Manual indication of a seizure may be achieved through anexternal activator device 22. The patient (or caregiver) may push abutton on the external device, while communicating with the implanteddevice. This will provide a marker and will initiate a recording, asdiscussed herein, of the sensed data (for example, in the event thepatient is experiencing a neurological event).

In treating SUDEP, for example, prolonged ECG recordings may be possible(e.g., recording all data during sleep since the incidence of SUDEP ishighest in patients during sleep). Post-processing of the signal canoccur in the implanted device, the patient's external device and/or inthe clinician external device. Intermittently (e.g., every morning,once/week, following a seizure), the patient may download data from theimplantable device to the patient external device (as will be discussedfurther herein), which may then be analyzed by the external device(and/or sent through a network to the physician) to assess any ECGabnormalities. If an abnormality is detected, the device may notify thepatient/caregiver. At that time, the patient/caregiver may inform thehealthcare provider of the alert to allow a full assessment of theabnormality. The clinician external device may also be capable ofobtaining the data from the implanted device and conducting an analysisof the stored signals. If a potentially life-threatening abnormality isdetected, the appropriate medical treatment may be prescribed (e.g.,cardiac abnormality: a pacemaker, an implantable defibrillator, or aheart resynchronization device may be indicated or respirationabnormality: CPAP, patient positioning, or stimulation of respirationmay be indicated).

FIG. 1 is a simplified schematic view of a core monitor 100 implanted ina patient 10. monitor 100 continuously senses and monitors one or morephysiological conditions of the patient via monitoring elements 140 (inthe embodiment, the physiological conditions are cardiac and respirationfunctions of patient 10 and the monitoring elements 140 are subcutaneouselectrodes). Stored diagnostic data is uplinked and evaluated by anexternal computing device 120 (e.g., a patient's physician utilizingprogrammer) via a 2-way telemetry link 132. An external patientactivator 122 may optionally allow the patient 10, or other careprovider (not shown), to manually activate the recording of diagnosticdata.

In the embodiment, monitor 100 encompasses monitoring elements 140 thatare several subcutaneous spiral electrodes and may be embeddedindividually into three or four recessed casings placed in a compliantsurround that is attached to the perimeter of implanted monitor 100 assubstantially described in U.S. Pat. Nos. 6,512,940 and 6,522,915. Theseelectrodes are electrically connected to the circuitry of the implantedmonitor 100 to allow the detection of cardiac depolarization waveforms(as substantially described in U.S. Pat. No. 6,505,067) that may befurther processed to detect cardiac electrical characteristics (e.g.,heart rate, heart rate variability, arrhythmias, cardiac arrest, sinusarrest and sinus tachycardia). Further processing of the cardiac signalssignal amplitudes may be used to detect respiration characteristics(e.g., respiration rate, minute ventilation, and apnea). To aid in theimplantation of monitor 100 in a proper position and orientation, animplant aid may be used to allow the implanting physician to determinethe proper location/orientation as substantially described in U.S. Pat.No. 6,496,715.

FIG. 2 depicts a block diagram of the electronic circuitry of the coremonitor 100 of FIG. 1 in accordance with an embodiment of the invention.Monitor 100 comprises a primary control circuit 220 and may be similarin design to that disclosed in U.S. Pat. No. 5,052,388. Primary controlcircuit 220 includes sense amplifier circuitry 224, a crystal clock 228,a random-access memory and read-only memory (RAM/ROM) unit 230, acentral processing unit (CPU) 232, a MV Processor circuit 238 and atelemetry circuit 234, all of which are generally known in the art.

Monitor 100 may include internal telemetry circuit 234 so that it iscapable of being programmed by means of external programmer/control unit120 via a 2-way telemetry link 132 (shown in FIG. 1). Externalprogrammer/control unit 120 communicates via telemetry with the monitor100 so that the programmer can transmit control commands and operationalparameter values to be received by the implanted device, and so that theimplanted device can communicate diagnostic and operational data to theprogrammer 120. For example, programmer 120 may be Models 9790 andCareLink® programmers, commercially available from Medtronic, Inc.,Minneapolis, Minn. Various telemetry systems for providing the necessarycommunications channels between an external programming unit and animplanted device have been developed and are well known in the art.Suitable telemetry systems are disclosed, for example, in U.S. Pat. Nos.5,127,404; 4,374,382; and 4,556,063.

Typically, telemetry systems such as those described in the abovereferenced patents are employed in conjunction with an externalprogramming/processing unit. Most commonly, telemetry systems forimplantable medical devices employ a radio-frequency (RF) transmitterand receiver in the device, and a corresponding RF transmitter andreceiver in the external programming unit. Within the implantabledevice, the transmitter and receiver utilize a wire coil as an antennafor receiving downlink telemetry signals and for radiating RF signalsfor uplink telemetry. The system is modeled as an air-core coupledtransformer. An example of such a telemetry system is shown in U.S. Pat.No. 4,556,063.

In order to communicate digital data using RF telemetry, a digitalencoding scheme such as is described in U.S. Pat. No. 5,127,404 can beused. In particular, a pulse interval modulation scheme may be employedfor downlink telemetry, wherein the external programmer transmits aseries of short RF “bursts” or pulses in which the interval betweensuccessive pulses (e.g., the interval from the trailing edge of onepulse to the trailing edge of the next) is modulated according to thedata to be transmitted. For example, a shorter interval may encode adigital “0” bit while a longer interval encodes a digital “1” bit. Foruplink telemetry, a pulse position modulation scheme may be employed toencode uplink telemetry data. For pulse position modulation, a pluralityof time slots are defined in a data frame, and the presence or absenceof pulses transmitted during each time slot encodes the data. Forexample, a sixteen-position data frame may be defined, wherein a pulsein one of the time slots represents a unique four-bit portion of data.

Programming units such as the above-referenced Medtronic Models 9790 andCareLink® programmers typically interface with the implanted devicethrough the use of a programming head or programming paddle, a handheldunit adapted to be placed on the patient's body over the implant site ofthe patient's implanted device. A magnet in the programming head effectsreed switch closure in the implanted device to initiate a telemetrysession. Thereafter, uplink and downlink communication takes placebetween the implanted device's transmitter and receiver and a receiverand transmitter disposed within the programming head.

As previously noted, primary control circuit 220 includes centralprocessing unit 232 which may be an off-the-shelf programmablemicroprocessor or microcontroller, but in an embodiment of the inventionis a custom integrated circuit. Although specific connections betweenCPU 232 and other components of primary control circuit 220 are notshown in FIG. 2, it will be apparent to those of ordinary skill in theart that CPU 232 functions to control the timed operation of senseamplifier circuit 224 under control of programming stored in RAM/ROMunit 230. Those of ordinary skill in the art will be familiar with suchan operative arrangement.

With continued reference to FIG. 2, crystal oscillator circuit 228, inan embodiment, is a 32,768-Hz crystal controlled oscillator, providesmain timing clock signals to primary control circuit 220. The variouscomponents of monitor 100 are powered by means of a battery (not shown),which is contained within the hermetic enclosure of monitor 100. For thesake of clarity in the figures, the battery and the connections betweenit and the other components of monitor 100 are not shown. Senseamplifier 224 is coupled to monitoring elements 140. Where cardiacintrinsic signals are sensed, they may sensed by sense amplifier 224 assubstantially described in U.S. Pat. No. 6,505,067.

Processing by CPU 232 allows the detection of cardiac electricalcharacteristics and anomalies (e.g., heart rate, heart rate variability,arrhythmias, cardiac arrest, sinus arrest and sinus tachycardia).Further processing of the cardiac signals signal amplitudes may be usedto detect respiration characteristics/anomalies (e.g., respiration rate,tidal volume, minute ventilation, and apnea) in Mv Processor 238.

FIG. 3 shows the intracardiac signals 370 presented to sense amplifier224 from monitoring elements 140. Note the amplitude variation ofcardiac signals caused by the change in thoracic cavity pressure due torespiration (i.e., inspiration and expiration). By low pass filteringthe cardiac signals 370, a signal representing minute ventilation may beobtained as depicted in waveform 372. This respiration signal mayfurther be examined to detect respiration rate and reduced or absence ofinspiration and expiration (central apnea) by CPU 232 and softwareresident in RAM/ROM 230.

Upon detection of either a cardiac or respiration anomaly, CPU 232,under control of firmware resident in RAM/ROM 230, will initiaterecording of the appropriate diagnostic information into RAM of RAM/ROM230 (discussed further herein), initiate a warning or alert to thepatient, patient caregiver, or remote monitoring location.

FIG. 4 is a flow diagram 400 showing operation of a core monitorsensing/monitoring cardiac and respiration parameters for the detectionof a neurological event as shown and described in FIG. 1 above.Beginning at block 402, the interval between sensed cardiac signals aremeasured. At block 404, a rate stability measurement is made on eachcardiac interval utilizing a heart rate average from block 406. At block408, a rate stable decision is made based upon preprogrammed parameters.If YES, the flow diagram returns to the HR Measurement block 402. If NO,the rate stability information is provided to Format Diagnostic Datablock 412.

At block 416, thoracic impedance is continuously measured in a samplingoperation. At block 418, a MV and respiration rate calculation is made.At block 420, a MV average calculation may be made and inputted to block418. At block 422, a pulmonary apnea decision is made based uponpreprogrammed criteria. If NO, the flow diagram returns to MVMeasurement block 416. If YES, the occurrence of apnea and MVinformation is provided to Format Diagnostic Data block 412. FormatDiagnostic Data block 412 formats the data from the cardiac andrespiration monitoring channels, adds a time stamp (i.e., date and time)410 and provides the data to block 414 where the data is stored in RAM,SRAM or MRAM memory for later retrieval by a clinician via telemetry(using the techniques discussed herein). Optionally, block 412 may addexamples of intrinsic ECG and/or respiration signals recorded during asensed neurological event. Additionally, optionally, block 415 mayinitiate a warning or alert to the patient, patient caregiver, or remotemonitoring location (as described in U.S. Pat. No. 5,752,976).

It will be appreciated that alternative embodiments of the core monitordevice may also be utilized. As discussed above, core monitor 100 maysense any number of physiologic conditions of the patient for purposesof detecting, and storing data relating to, any number of theneurological events. For example, cardiac lead(s) may be used tofacilitate detection of a neurological event and the recording of dataand signals pre and post event. Cardiac leads may consist of any typicallead configuration as is known in the art, such as, without limitation,right ventricular (RV) pacing or defibrillation leads, right atrial (RA)pacing or defibrillation leads, single pass RA/RV pacing ordefibrillation leads, coronary sinus (CS) pacing or defibrillationleads, left ventricular pacing or defibrillation leads, pacing ordefibrillation epicardial leads, subcutaneous defibrillation leads,unipolar or bipolar lead configurations, or any combinations of theabove lead systems.

In another embodiment, an electrode located distally on a sensor stubmay be used to facilitate detection of a neurological event and therecording of data and signals pre and post event. The sensor stub isinserted subcutaneously in a thoracic area of the patient. The monitor100 may sense cardiac signals between an electrode on the distal end ofthe sensor stub and the monitor case as described in conjunction withthe embodiment shown in FIG. 5 in U.S. Pat. No. 5,987,352. The monitor100 may also sense respiration parameters such as respiration rate,minute ventilation and apnea via measuring and analyzing the impedancevariations measured from the implanted monitor 100 case to the electrodelocated distally on the sensor stub lead as substantially described inU.S. Pat. Nos. 4,567,892 and 4,596,251.

In yet another embodiment, an external wearable device such as awearable patch, a wristwatch, or a wearable computing device may be usedmay be used to continuously sense and monitor cardiac and respirationfunction of patient 10. Optionally, a button on the external wearabledevice may be activated by the patient 10 (or a caregiver) to manuallyactivate data recording (for example, in the event the patient isexperiencing a neurological event). The external wearable device maycomprise an amplifier, memory, microprocessor, receiver, transmitter andother electronic components as substantially described in U.S. Pat. No.6,200,265. In the embodiment of a wearable patch, the device may consistof a resilient substrate affixed to the patient's skin with the use ofan adhesive. The substrate flexes in a complimentary manner in responseto a patient's body movements providing patient comfort and wearability.The low profile patch is preferably similar in size and shape to astandard bandage, and may be attached to the patient's skin in aninconspicuous location.

FIG. 5 shows an apparatus 500 for collecting physiologic data that canbe retained in accordance with an embodiment of the invention. Apparatuscomprises implanted device 501 and external device 503. In theembodiment, implanted device 501 collects physiological data through EEGlead 505, which is coupled to an electrode. The embodiment may support aplurality of electrodes that may collect physiological data from desiredlocations in the brain or other neural tissue within the body. Withrespect to sensing of the brain, the embodiment may support electrodesthat are positioned in the brain, positioned on the scalp, or acombination. EEG amplifier 521 processes neurological signals from EEGlead 505, while stimulator 511 forms appropriate electrical waveforms tosimulate electrodes that are coupled to EEG lead 505. CPU 513 controlsthe circuitry in internal device 501 and is clocked by crystal clock519. CPU 513 obtains instructions from and stores neurological data toRAM/ROM 515. Communication within internal device between components istransported on I/O bus 523.

External device 503 collects other physiologic data through patch leads507 a and 507 b, which are coupled to patch electrodes. External device503 is typically worn by the patient. In the embodiment, the patchelectrodes monitor and stimulate the respiration of the patient inconcert with monitoring neurological data. Respiratory data is collectedfrom the patch electrodes through lead interface 525. Minute Ventilation(MV) module 527 excites the patch electrodes (if necessary) whilerespiratory data (indicative of the minute ventilation) is obtainedthrough sense amplifier 531. (Minute or total ventilation is the productof respiratory rate and tidal volume.) Additionally, impedance module529, MV low pass filter 533, and MV calibration module 535 calibrate MVexcitation module 527. Data communication within external device 503 istransported on I/O bus 539.

Internal device 501 and external device 503 communicate with each otherover telemetry channel 543 through telemetry interfaces 517 and 537 andantennas 539 and 541. However, internal device 501 and external device503 may communicate using an alternative communications path. Forexample, I/O bus 523 and I/O bus 539 may be electrically connectedthrough a wired channel.

While the embodiment shown in FIG. 5 collects and retains physiologicaldata and respiratory data, other physiologic data may be collected andretained. For example, apparatus 500 may collect cardiac data and motorcoordination data. The embodiment may further correlate the neurologicaldata with the physiological data.

Full Monitor

The full monitor is capable of monitoring cardiopulmonary parameters asin the core monitor described above, and additionally an EEG from anintracranially implanted lead system. This will allow the full monitorto collect cardiovascular, respiratory and neurologic signals in closeproximity to detected neurologic events as well as notifying thepatient/caregiver of a prolonged event (and/or status epilepticus). Likethe core monitor, cardiovascular and respiratory monitoring may occuraround a neurologic event (peri-ictal). The full monitor device maydetect the neurological event and analyze the peri-ictal signals andinitiate loop recording. The addition of the neurologic monitor allowsshorter loop-recording durations since the beginning of the neurologicalevent may be known with greater certainty. In addition, the EEGmonitoring may be programmed to provide alerts when a neurologic eventhas exceeded a pre-determined duration or severity.

FIG. 6 is a simplified schematic view of a full monitor 620 implanted ina patient 10. Monitor 620 continuously senses and monitors cardiac,brain and respiration function of patient 10 via several subcutaneouselectrodes 616 and a brain lead 618 to allow detection of neurologicalevents and the recording of data and signals pre and post event. Storeddiagnostic data is uplinked and evaluated by the patient's physicianutilizing programmer 612 via a 2-way telemetry link 632. An externalpatient activator 622 may optionally allow the patient 10, or other careprovider (not shown), to manually activate the recording of diagnosticdata. An implant aid may be used with monitor 620 to ensure a properposition and orientation during implant as described above in connectionwith the system of FIG. 1.

FIG. 7 is a block diagram of the electronic circuitry that makes up fullmonitor 620 with brain lead 618 and cardiac leads 616 of FIG. 6 inaccordance with the disclosed alternative embodiment of the invention.Cardiac leads 616V represent the grouping of VTIP and VRING. Cardiacleads 616A represent the grouping of ATIP and ARING. Monitor 620comprises a primary control circuit 720 and MV circuit 722 that aredescribed herein above in conjunction with FIG. 2. In addition, the fullMonitor 620 also includes an amplifier 725 to amplify and sense EEGsignals from a cranially implanted lead 618. The CPU 732, in conjunctionwith a software program resident in RAM/ROM 730, integrates theinformation from the sensed cardiac, respiration and EEG signals,detects the onset of cerebral, cardiac and/or respiratory anomalies,formats and stores diagnostic data for later retrieval by the patient'sclinician and, optionally, may warn or alert the patient, patientcaregiver or remote monitoring location. Sense amplifier circuit 724 islike sense amplifier circuit 224 in FIG. 2. Crystal clock 728 is likecrystal clock 519 in FIG. 5. Telemetry interface 734 is like telemetryinterface 517 in FIG. 5. Antenna 736 is like antenna 519 in FIG. 5. I/Obus 740 is like I/O bus 523 in FIG. 5. I/O bus 742 is like I/O bus 539in FIG. 5. MV calibration module 752 is like MV calibration module 535in FIG. 5. MV low pass filter 750 is like MV low pass filter 533 in FIG.5. Impedance module 748 is like impedance module 529 in FIG. 5. MVexcitation module 746 is like MV excitation module 527 in FIG. 5. Leadinterface 744 is like lead interface 525 in FIG. 5. Communication link738 connects additional I/O buses or other devices.

FIG. 8 is a flow diagram 840 showing operation of a full monitor sensingand monitoring cardiac, respiration and electroencephalogram parametersfor the detection of a neurological event as shown and described inembodiment in FIG. 6 above. Beginning at block 802, the interval betweensensed cardiac signals are measured. At block 804, a rate stabilitymeasurement is made on each cardiac interval utilizing a heart rateaverage from block 806. At block 808, a rate stable decision is madebased upon preprogrammed parameters. If YES, the flow diagram returns tothe HR Measurement block 802. If NO, the rate stability information isprovided to Format Diagnostic Data block 812.

At block 816, thoracic impedance is continuously measured in a samplingoperation. At block 818, a MV and respiration rate calculation is made.At block 820, a MV average calculation may be made and inputted to block818. At block 822, a pulmonary apnea decision is made based uponpreprogrammed criteria. If NO, the flow diagram returns to MVMeasurement block 816. If YES, the occurrence of apnea and MVinformation is provided to Format Diagnostic Data block 812.

At block 824, the electroencephalogram is sensed and measured. An EEGseizure determination is performed at block 826 as described in U.S.Pat. No. 7,280,867. At block 828, a seizure cluster episode isdetermined. If NO, the flow diagram returns to EEG Measurement block824. If YES, the occurrence of a seizure cluster is provided to FormatDiagnostic Data block 812. Format Diagnostic Data block 812 formats thedata from the cardiac, respiration and EEG monitoring channels, adds atime stamp (ie, date and time) and provides the data to block 814 wherethe data is stored in RAM memory for later retrieval by a clinician viatelemetry (using techniques discussed herein). Optionally, block 812 mayadd examples of intrinsic ECG, respiration and/or EEG signals recordedduring a sensed episode/seizure. Additionally, optionally, block 815 mayinitiate a warning or alert to the patient, patient caregiver, or remotemonitoring location (as described in U.S. Pat. No. 5,752,976).

Again, it will be appreciated that alternative embodiments of the fullmonitor device may also be utilized. For example, cardiac lead(s), asensor stub, and/or a wearable patch may be used to facilitate detectionof a neurologic event and the recording of data and signals pre and postevent. An integrated electrode may also be used that senses ECG signalsas described in U.S. Pat. No. 5,987,352 and respiration signals asdescribed in U.S. Pat. Nos. 4,567,892 and 4,596,251. Optionally, themonitor may warn/alert the patient 10 via buzzes, tones, beeps or spokenvoice (as substantially described in U.S. Pat. No. 6,067,473) via apiezo-electric transducer incorporated in the housing of monitor andtransmitting sound to the patient's inner ear.

In another embodiment, the monitor may be implanted cranially in thepatient 10. In such an embodiment, the monitor may be constructed assubstantially described in U.S. Pat. Nos. 5,782,891 and 6,427,086. EEGsensing may be accomplished by the use of integrated electrodes in thehousing of the monitor, cranially implanted leads, and or leadless EEGsensing.

Alternatively, ECG rate and asystole may be inferred using a variety oftechnologies. For example, ECG rate and asystole may be inferred (alongwith a blood pressure signal) from a capacitive dynamic pressure signal(i.e., dP/dt) as substantially described in U.S. Pat. No. 4,485,813.Similarly, an acoustic signal (i.e., sound) may be used as substantiallydescribed in U.S. Pat. No. 5,554,177 (the sensed acoustic signal is lowpass filtered to limit ECG signals to 0.5-3 Hz while filtering outspeech, swallowing and chewing sounds). As another example, ECG rate andasystole may be inferred (along with a blood saturation measurement) bymonitoring a reflectance oximetry signal (i.e., O₂sat) as substantiallydescribed in U.S. Pat. No. 4,903,701. As yet another example, a bloodtemperature signal (i.e., dT/dt) may be used as substantially describedin U.S. Pat. No. 5,336,244. As still another example, ECG rate andasystole may be inferred (along with an arterial flow measurement) bymonitoring a blood flow signal (from an adjacent vein via impedanceplethysmography, piezoelectric sensor or Doppler ultrasound) assubstantially described in U.S. Pat. No. 5,409,009. As another example,ECG rate and asystole may be inferred (along with a blood pressuremeasurement) by monitoring a blood pressure signal utilizing a straingauge s substantially described in U.S. Pat. No. 5,168,759. As anotherexample, ECG rate and asystole may be inferred by monitoring a bloodparameter sensor (such as oxygen, pulse or flow) located on a V-shapedlead as substantially described in U.S. Pat. No. 5,354,318.

Monitor and Treat

As exemplified above, any number of implantable medical device systemsare envisioned that may incorporate the recording and retentiontechniques discussed herein. For example, the monitoring may be achievedusing any of the above techniques in conjunction with treatment bydelivery of treatment therapy (e.g., electrical stimulation) to thebrain, cardiac or respiration.

FIG. 9 is a simplified schematic view of a full Monitor/Brain,Respiration and Cardiac Therapy unit 980 implanted in a patient 10.Monitor/Brain, Respiration and Cardiac Therapy unit 980 continuouslysenses and monitors cardiac, brain and/or respiration function ofpatient 10 via cardiac lead(s) 916 and a brain lead 918 to allowdetection of epileptic neurological events, the recording of data andsignals pre and post event, and the delivery of therapy via brain lead918, cardiac lead(s) 916 and phrenic nerve lead 928. Stored diagnosticdata is uplinked and evaluated by the patient's physician utilizingprogrammer 912 via a 2-way telemetry link 932. An external patientactivator 922 may optionally allow the patient 10, or other careprovider (not shown), to manually activate the recording of diagnosticdata and delivery of therapy. Optionally, lead 928 may connect to thediaphragm to provide direct diaphragmatic stimulation. As discussed anycombination of monitoring and any combination of treatment may beimplemented.

FIG. 10 is a block diagram of the electronic circuitry that makes upfull Monitor/Brain, Respiration and Cardiac Therapy device 980 of FIG.9. Monitor/Brain, Respiration and Cardiac Therapy device 980 comprises aprimary control circuit 1020 and MV circuit 1022 whose function wasdescribed herein above in conjunction with FIG. 2. In addition theMonitor/Brain, Respiration and Cardiac Therapy device of FIG. 10 alsoincludes an amplifier 1025 to amplify and sense EEG signals from acranially implanted lead 918 and an output stimulator 1029 to providebrain stimulation via cranially implanted lead 918 and phrenic nervestimulation via respiration lead 928. The CPU 1032, in conjunction withsoftware program in RAM/ROM 1030, integrates the information from thesensed cardiac, respiration and EEG signals, detects the onset ofcerebral, cardiac and/or respiratory anomalies, provides preprogrammedstimulation therapy to the patient's brain via lead 918, stimulation ofthe patient's phrenic nerve via respiration lead 928 and stimulation ofthe patient's heart via cardiac leads 916, formats and stores diagnosticdata for later retrieval by the patient's clinician and, optionally, maywarn or alert the patient, patient caregiver or remote monitoringlocation. Cardiac leads 916V represent the grouping of VTIP and VRING.Cardiac leads 916A represent the grouping of ATIP and ARING. Optionally,lead 928 may connect to the diaphragm to provide direct diaphragmaticstimulation. Sense amplifier circuit 1024 is like sense amplifiercircuit 224 in FIG. 2. Crystal clock 1028 is like crystal clock 519 inFIG. 5. Telemetry interface 1034 is like telemetry interface 517 in FIG.5. Antenna 1036 is like antenna 519 in FIG. 5. I/O bus 1040 is like I/Obus 523 in FIG. 5. I/O bus 1042 is like I/O bus 539 in FIG. 5. MVcalibration module 1052 is like MV calibration module 535 in FIG. 5. MVlow pass filter 1050 is like MV low pass filter 533 in FIG. 5. Impedancemodule 1048 is like impedance module 529 in FIG. 5. MV excitation module1046 is like MV excitation module 527 in FIG. 5. Lead interface 1044 islike lead interface 525 in FIG. 5. Communication link 1038 connectsadditional I/O buses or other devices.

FIG. 11 is a flow diagram 1150 showing operation of a fullmonitor/therapy sensing and monitoring cardiac, respiration andelectroencephalogram parameters as shown and described in FIG. 9 above.Beginning at block 1102, the interval between sensed cardiac signals aremeasured. At block 1104, a rate stability measurement is made on eachcardiac interval utilizing a heart rate average from block 1106. Atblock 1108, a rate stable decision is made based upon preprogrammedparameters. If YES, the flow diagram returns to the HR Measurement block1102. If NO, the rate stability information is provided to DetermineTherapy and Duration block 1130.

At block 1116, thoracic impedance is continuously measured in a samplingoperation. At block 1118, a MV and respiration rate calculation is made.At block 1120, a MV average calculation may be made and inputted toblock 1118. At block 1122, a pulmonary apnea decision is made based uponpreprogrammed criteria. If NO, the flow diagram returns to MVMeasurement block 1116. If YES, the occurrence of apnea and MVinformation is provided to Determine Therapy and Duration block 1130.

At block 1124, the electroencephalogram is sensed and measured. An EEGcalculation is performed at block 1126. At block 1128, a seizure episodeis determined. If NO, the flow diagram returns to EEG Measurement block1124. If YES, the occurrence of a seizure is provided to DetermineTherapy and Duration block 1130.

Based upon the data presented to it, Determine Therapy and Durationblock 1130 determines the type of therapy and the duration to block1132, which controls the start of the therapy by evaluating the severityand ranking of each event (i.e., maximum ratio, duration of seizuredetection, spread, number of clusters per unit time, number ofdetections per cluster, duration of an event cluster, duration of adetection, and inter-seizure interval). Block 1134 monitors thecompletion of the determined therapy. If the therapy is not complete,block returns to block 1134. If the therapy is determined to becomplete, block 1134 returns the flow diagram to blocks 1102 (MeasureHR), 1116 (Measure Impedance) and 1124 (Measure EEG) to continue themonitoring of cardiac, respiratory and brain signal parameters. Therapymay consist of neural stimulation, cardiac pacing,cardioversion/defibrillation, and drug delivery via a pump or anycombination of therapies.

When block 1130 determines that a therapy is to be initiated FormatDiagnostic Data block 1112 formats the data from the cardiac,respiration and EEG monitoring channels, adds a time stamp (i.e., dateand time) 1110, type and duration of therapy and provides the data toblock 1114 where the data is stored in RAM memory for later retrieval bya clinician via telemetry (using techniques discussed herein).Optionally, block 1112 may add examples of intrinsic ECG, respirationand/or EEG signals recorded during a sensed episode/seizure. Block 1115is like block 415 in FIG. 4. Block 1120 is like block 420 in FIG. 4.

The above embodiments illustrate that the disclosed techniques may beimplemented within any number of medical device systems (drug delivery,electrical stimulation, pacemaking, defibrillating, cochlear implant,and/or diagnostic) but configured to retain sensed data records inaccordance with the teachings disclosed herein. In general, theimplanted medical component utilizes one or more monitoring elements(e.g., electrodes or other sensors), a memory component having aplurality of data structures (and/or data structure types), a processingcomponent (such as a CPU) to process received data for storage in memoryas disclosed herein, and a telemetry component.

Data Reporting and Remote Monitoring

FIG. 12 shows apparatus 1200 that supports reporting physiological datain accordance with an embodiment of the invention. With apparatus 1200,the implanted component 1205 of the medical device system communicateswith the relaying module 1215 via telemetry antenna 1210. Similarly, theexternal component 1225 communicates with the relaying module 1215 viaantenna 1220. The external component 1225 may include an audio output1230 as illustrated in FIG. 12. In the embodiment, a telemetry link 1221between relaying module 1215 and antenna 1220 comprises a 3 MHz bodywave telemetry link. To avoid interference, the relaying module 1215 maycommunicate with the external and implanted components using differingcommunication schemes. In some embodiments, the reverse direction andthe forward direction of telemetry link 1221 may be associated withdifferent frequency spectra. The relaying module 1215 thereby provides agreater range of communications between components of medical devicesystem. For example, in the embodiment of an implanted system, anexternal programmer may communicate with an implanted device from a moreremote location. The external programmer may be across the room andstill be in communication via the relaying module 1215. With thetelemetry booster stage, the use of an implanted system is moreconvenient to the patient, in particular at night while sleeping or whentaking a shower, eliminating the need for an external device to be wornon the body. In an embodiment, relating module 1215 may also have thefeatures and functionality of external device 503 as shown in FIG. 5.Moreover, in an embodiment a physician programmer 1235 may communicatewith external component 1225.

As shown in FIG. 13, in an embodiment, the system allows theresidential, hospital or ambulatory monitoring of at-risk patients andtheir implanted medical devices at any time and anywhere in the world.Medical support staff 1306 at a remote medical support center 1314 mayinterrogate and read telemetry from the implanted medical device andreprogram its operation while the patient 10 is at very remote or evenunknown locations anywhere in the world. Two-way voice communications1310 via satellite 1304, cellular via link 1332 or land lines 1356 withthe patient 10 and data/programming communications with the implantedmedical device 1358 via a belt worn transponder 1360 may be initiated bythe patient 10 or the medical support staff 1306. A portion of theequipment used to establish cellular link 1332 or land lines 1356 may behoused at a location 1312. The location of the patient 10 and theimplanted medical device 1358 may be determined via GPS 1302 and link1308 and communicated to the medical support network in an emergency.Emergency response teams can be dispatched to the determined patientlocation with the necessary information to prepare for treatment andprovide support after arrival on the scene. See for example, U.S. Pat.No. 5,752,976.

An alternative or addition to the remote monitoring system as describedabove in conjunction with FIG. 13 is shown in the system 1450 of FIG.14, which shows a patient 10 sleeping with an implantable Monitor 1458and/or optional therapy device as described above in connection with theabove-described systems. The implantable device 1458, upon detection ofa neurologic event may alert a remote monitoring location via localremote box 1452 (as described in U.S. Pat. No. 5,752,976), telephone1454 and phone lines 1456 or the patient's care provider via an RF link1432 to a pager-sized remote monitor 1460 placed in other locations inthe house or carried (i.e., belt worn) by the care provider 1462. Theremote caregiver monitor 1460 may include audible buzzes/tones/beeps,vocal, light and/or vibration to alert the caregiver 1462 of patient'smonitor in an alarm/alert condition. The RF link may include RF portablephone frequencies, power line RF links, HOMERF™ wireless, BLUETOOTH™wireless, ZIGBEE™ wireless, WIFI, MICS band (medical implantcommunications service), or any other interconnect methods asappropriate.

Each of the above embodiments utilized graphical user interfaces thatare suitable for displaying data records that have been retrieved fromthe implantable medical device.

Data Retention and Recording Techniques

Discussed herein are techniques for selecting and storing sensedphysiological data in an implanted medical device for subsequentreporting to an external device. As used herein, the term data recordencompasses the sensed physiological data, summary information, orsimply a pointer that references a location in memory where the sensedphysiological data is stored. Thus, the concept of storage of datarecords in first and second data structures envisions possibilities ofstorage of the sensed physiological data and the storage of theirassociated pointers. As an example, summary information data may bestored in the first and second data structures wherein the more detailedand more space consuming waveform data (pre-detection data,post-detection data, etc.) may be stored, and pointed to, in anassociated memory (such as a loop record buffer).

Mapping from entries in the first and second data structures to thewaveform physiological data that is stored in the associated memory maybe achieved with pointers. Each entry in the event log may point to itscorresponding waveform data, or each waveform data may point to itscorresponding data in the event log. Alternatively, multi-directionalpointers in an “allocation table” or “allocation data structure” may bepointed to by the priority structures. Thus, when a data record isoverwritten or replaced as discussed herein, both the data record itselfand its mapping to the event log may be changed/removed in theallocation structure.

FIG. 15 shows process 1500 for storing physiological data in accordancewith an embodiment of the invention. Again, the techniques disclosedherein may be implemented in any of the implantable medical devicesystems discussed above and may be performed in conjunction with theflow diagrams of FIGS. 4, 8, and 11 above. The process described thereinmay be implemented by computer executable instructions performed by aprocessor or dedicated hardware in the form of digital logic gates (alsoreferred as hardware rather than software/firmware) in the implanteddevice. (Process 1500 may be performed by a logic component that mayinclude a processor and/or digital logic such as an ASIC.) The processdescribed herein discusses the storage of data records within one ormore data structures and the moving of those data records. It will beappreciated, however, that these processes may be implemented by storageand movement of pointers, wherein each pointer points to data that isstored in memory, and/or the storage and movement of the sensedphysiological data.

The technique for storing data records may begin with step 1501, whereinan implanted device receives an instruction or configuration data from aclinician, typically via telemetry. For example, the clinician orpatient may activate loop recording to store data collected for aspecified neurological event between a specified time and having aminimum severity level (as will be discussed). In step 1503, animplanted device initiates a detection process for a neurological event.This detection process may implement an event detection algorithm toprocess the sensed physiological data and determine the possible onsetof a neurological event. The neurological event may be associated with anervous system disorder (e.g., an epileptic seizure) having a severitylevel and a time duration. The neurological event may also be a cardiacevent. For example, a patient's heart rate may increase with anoccurrence of an epileptic seizure. Accordingly, the implanted devicemay initiate loop recording upon determination of a neurological eventby processing of sensed physiologic signals or upon determination of anynumber of other criteria.

By way of example only, the system may monitor one set of physiologicalsignals (e.g., EEG) and trigger loop recording of those same signalsupon detection of a neurological event. As another example, the systemmay monitor any combination of a plurality of physiological signals(including EEG, respiratory, and cardiac) and trigger loop recording ofonly a subset of those physiological signals based on predeterminedcriteria being satisfied with respect to one or more of the otherphysiological signals.

In an embodiment, the implantable medical device may have a set ofmonitoring elements sensing brain activity and another set of monitoringelement that sense a physiological activity other than the brain (e.g.,heart activity such as a heart arrhythmia and/or respiratory activity).The device may then implement a detection algorithm to determine thepossible onset of a possible neurological event (e.g., a seizure) basedon the sensed signals from either the first or second monitoringelements. Once a neurological event is detected, data records associatedwith the first and second monitoring elements may be stored in memory inaccordance with the teachings herein.

Alternatively or additionally, the device may initiate loop recordingupon indication to do so by the patient based, for example, on a patientdetecting a neurological event. In the event the patient initiates looprecording based on detection of a neurological event (wherein, however,the detection process of the implanted device has not detected theneurological event), the priority index (discussed below) for such datamay be set at a higher level such that the data is stored in a memory.In the situation where the patient experiences a neurological event butthe medical device has not detected the event, the physiological senseddata may be particularly important for storage and subsequentevaluation. In an embodiment, once activated by a patient, looprecording may save the data for 30 seconds before the indicated seizureand 3 minutes after the seizure. However, to allow for the fact that thepatient may not mark the seizure until the seizure has ended, the ECGloop recording may begin 3 to 5 minutes before the patient mark. Thistime period may be programmable. As discussed below, a subset or acomposite of physiologic channels is selected from the availablephysiologic channels based on a selection criterion.

Referring still to FIG. 15, if the detected neurological event meets thecriterion provided by the clinician, the system triggers loop recordingin step 1505. In step 1507, the implanted device stores a data recordassociated with the sensed physiological data in a first data structure(in an embodiment, a circular buffer as will be discussed in greaterdetail in FIG. 16). Again, the data record may either be a pointer orthe physiological data. An exemplary data entry is discussed below inrelation to FIGS. 18 and 19. In an embodiment, the circular bufferstores chronologically sequenced data records in sequential memorylocations. When the last location in the circular buffer is reached, thenext data record is entered in the first memory location of the circularbuffer. Although the embodiment of FIG. 15 and the correspondingdiscussion herein is with respect to a circular buffer, it will beappreciated that the circular buffer may be any memory device orstructure and the data records may be stored and replaced according toan associated priority index (discussed below). When the memory deviceis full, any new data may replace data in the memory device having thelowest associated priority index. Alternatively, as discussed below, thedata may be automatically transferred out once the priority index iscalculated.

With the storage of neurological data in step 1507, the implanted devicemay also obtain and retain indicators of severity when the neurologicalevent occurs in step 1509. Examples of retained indicators include amaximum value of foreground ictal severity and heart rate during theneurological event. Indicators of severity are discussed further belowand may be used to determine a priority index.

If the first data structure becomes full, a new data record replaceseither the oldest data record or the existing data record having thelowest associated priority index. However, in step 1511, if theassociated priority index of the data record being replaced by the newdata record is sufficiently large, the data record being replaced may bestored in a priority buffer instead of being permanently removed. Itwill be appreciated, that the data records may vary in size.Accordingly, for a new data record having a sufficiently large size, thesystem may require multiple old data record to be removed.Alternatively, only the least important portions of the data recordwould need to be removed from the first data structure.

The priority index of a data entry, discussed next, is determined insteps 1515, 1517, and 1519 in concert with clinician input andinformation obtained by the implanted device. In the embodiment of theinvention, steps 1507, 1509, and 1511 are executed in a parallel manner.In step 1513, the recording of neurological and other physiological datain the circular buffer is completed. In an alternative embodiment, thedata entry may be transferred from the first data structure (such as thecircular buffer) to the second data structure (priority buffer) upon thepriority index of the data entry being determined. In such anembodiment, the second data structure may begin to be populated withdata records without requiring for the first data structure to becomefull and start replacing older data entries. Since the stored data entryis promptly removed to the second data structure, the circular buffermay vary in size.

One embodiment for determining the priority index of a data record is asfollows. In step 1515, the most recent data record is classified. Forexample, the neurological event may be classified as an epilepticseizure. In step 1517, a priority index of the neurological event isdetermined. The priority index may be dependent on a severity level. Inan embodiment, the severity level is a function of at least onecharacteristic of the neurological event, including the duration,spread, and measure of ictal content (e.g., peak ratio ofalgorithmically derived foreground to background ictal score) of theneurological event. Moreover, the embodiment may utilize otherderivative indicators for determining the severity level. For example, abinary evidence count may be determined in which each new sample iscompared to a criterion (e.g., a threshold determined by the product ofa background value and a configured threshold value). If the criterionis met, a value of “1” is inserted into a data structure that contains Yprevious Boolean values. Otherwise, if unmet, a value of “0” is insertedinto the data structure. Upon insertion, a second value is removed fromthe data structure to ensure that the data structure retains a size of Ybits. The Boolean value of the first sample is then compared to theBoolean value of the second sample. The difference is used to maintain aseparate counter value which reflects how many Boolean values in thedata structure (e.g., Y-bit buffer) are “1”. In this way, the evidencecount reflects the number of samples out of the last Y samples which metthe threshold criterion, and therefore ranges from 0 to Y.

As another example, a slew-rate limited output of an associatedphysiologic channel may be determined by incrementing the slew-ratelimited output by a small amount if the sample is greater than thecurrent value of the slew-rate limited output. Otherwise, the slew-ratelimited output is decremented by the small amount. The severity levelmay be determined from the maximum value of the evidence count or theslew-rate limited output associated with the set of physiologic channelscontained in a data record.

In addition, the priority index of the neurological event may bedependent on an associated event, e.g., a cardiac event or a user signalin the form of telemetry, presence of a medical magnet, and so forth. Inan embodiment, the priority index is stored in a data field in the datarecord. However, another embodiment of the invention may store thepriority index in an associated data structure or may be calculated whenit is needed.

In step 1519, a composite severity measure of a group of neurologicalevents, which includes the current neurological event, is determined.The composite severity measure may be a function of determined severitylevels of individual events and the relative chronological occurrence ofevents. For example, a group of epileptic seizures that occur within ashort period time may be indicative of a more significant cumulativeevent than a single epileptic seizure. Next, in step 1521 the processmay wait for the next loop recording trigger before returning to step1503.

While the embodiment illustrated in FIG. 15 shows a sequential orderingof steps, it will be appreciated (as discussed above) that the processmay execute the steps in a different order or may execute some of thesteps in a parallel fashion.

The priority index may be dependent on the severity level, which may beexpressed as a function f(x₁, x₂, . . . , x_(n)), and/or on associatedfactors, which may be expressed as a function g(y₁, y₂, . . . y_(m)).Variable x_(i) corresponds to a characteristic of a physiologic event(e.g., a neurological event), and variable y_(j) is an associatedfactor. For example, characteristics of a neurological event may includea duration of a neurological cluster, a spread of a neurological cluster(which may be measured by the number of electrodes detecting thecluster), a statistic of an associated neurological signal, and an eventclass. A statistic may be a computed quantity characteristic of aphysiologic signal or an ensemble of physiologic signals. An event classmay include a most-severe seizure (potentially correlating to statusepilepticus), a severe seizure, a sub-clinical seizure, a least severeseizure (potentially correlating to what is more likely to be anerroneous detection), a brady event, a tachy event, arrhythmia, and adetection on each electrode channel.

An associated event may include external event information andassociated physiologic information that are correlated to a neurologicalevent. For example, the associated physiologic information may be theage of the event. As another example, an external event may be a cardiacevent, a chemical event, a scheduling event, a patient-initiated event(through a physical interface, e.g., a magnet interface or a telemetryinterface), a caregiver-initiated event (e.g. through a telemetrychannel), and a device-based event. Associated physiologic informationmay include heart rate, blood pressure, breathing rate, and glucoselevel. Moreover, an external event may not be associated with aneurological event. For example, a physician may instruct, through aprogrammer, that physiologic data for a designated time be stored andreported.

The priority index may be expressed as a mathematical combination of theseverity level function f(x₁, x₂, . . . , x_(n)) and the associatedfactor function g(y₁, y₂, . . . y_(m)). For example, the priority levelmay be expressed as:priority index=f(x ₁ ,x ₂ , . . . ,x _(n))+g(y ₁ ,y ₂ , . . . y_(m))  (EQ. 1A)Either f(x₁, x₂, . . . , x_(n)) or g(y₁, y₂, . . . y_(m)) may be acontinuous function, a discrete-value function, a Boolean function, or acombination of the above function types. As another example, thepriority level may be expressed as:priority index=f(x ₁ ,x ₂ , . . . ,x _(n))·g(y ₁ ,y ₂ , . . . y_(m))  (EQ. 1B)The priority index may be more generally expressed as a functionh(z₁,z₂), wherepriority index=h(f(x ₁ ,x ₂ , . . . ,x _(n)),g(y ₁ ,y ₂ , . . . y_(m)))  (EQ. 1C)

FIG. 16 shows data structure 1600 for storing physiological data inaccordance with an embodiment of the invention. In this embodiment, datastructure 1600 includes circular buffer 1601 and priority queue 1603.(Another embodiment of the invention may implement circular buffer 1601and/or priority queue 1603 as a different type of data structure.)Circular buffer 1601 stores the most recent ten data records (DATA(-2)to DATA(-3) corresponding to data entries 1607-1625). (An exemplaryrecord is discussed with FIG. 18.) However, the embodiment may store adifferent number of data records, depending on the allocated memory forcircular buffer 1601. In the example shown, circular buffer 1601currently stores data records that have been acquired between theprevious nine time units (corresponding to data record DATA(-9)) and thecurrent time (corresponding to data record DATA(0)). New data pointer1605 points to a data entry in circular buffer 1601. At the currenttime, new data pointer 1605 points to the data entry where new data isstored. Previous to storing data record DATA(0), data entry 1611 storeddata record DATA(-10), which was previously acquired 10 time units ago.The new data record may be associated with physiologic signals and maybe further associated with a neurological event. With the nextsubsequent data acquisition, new data pointer 1605 will point to thenext data entry that currently stores data record (DATA(-9)). In theembodiment, the new data record is stored in the data entry that storesthe oldest data record. When last data entry 1625 (currentlycorresponding to data record DATA(-3)) of circular buffer 1601 isreached, the subsequent data acquisition is stored in data entry 1607currently storing data record DATA(-2).

As discussed, the data record may be the sensed physiological data or apointer that references a location in memory where the sensedphysiological data is stored. Thus, the concept of storage of datarecords in first and second data structures envisions both possibilitiesof storage of the sensed physiological data and the storage of theirassociated pointers. Also as discussed, circular buffer 1601 may be inthe form of any other data structure. In such an alternative embodiment,physiological data may be stored in a memory device such that when a newdata record is to replace an existing data record, the data record withthe lowest priority index is replaced. Alternatively, the data entriesbeing replaced may vary depending on the relative sizes of the new andold data entries.

When a data record has been overwritten by the new data record, aportion of the old data record (which may be the entire data record) isstored in priority queue 1603 if the corresponding priority index issufficiently large or exceeding a threshold criterion. In oneembodiment, the more significant the corresponding physiologic event,the larger the corresponding priority index. However, in anotherembodiment the priority level may decrease with the significance of thephysiologic event. Priority queue 1603 is capable of storing datarecords in data entries 1627-1635; however, as shown in the example,priority queue 1603 currently stores two data records. The remainingdata entries 1631, 1633, and 1635 are empty and may store subsequentdata acquisition. Data entry 1627 is currently storing data recordDATA(−101), which was acquired 101 time units ago, and data entry 1629is currently storing data record DATA(−24), which was acquired 24 timeunits ago. For example, the priority index must have a value of 3 orhigher in order to be stored in priority queue 1603 when thecorresponding data record is overwritten in circular buffer 1601. In theevent that the priority queue 1603 is also filled, the system maydetermine that a data record shall be retained in priority queue 1603only if the priority index of the removed data record from circularbuffer 1601 has a larger priority index than any of the stored dataentries in priority queue 1603. In other embodiments, the system mayutilize a combination of the above retention strategies or otherstrategies.

In an embodiment of the invention, a data record (stored in data entries1607, 1609, 1611, 1613, 1615, 1617, 1619, 1621, 1623, and 1625) incircular buffer 1601 may contain a different amount of data than a datarecord (stored in data entries 1627, 1629, 1631, 1633, and 1635) inpriority queue 1603. For example, data may be discarded to reduce theprecision or to discard physiologic data that is not directly associatedwith a neurological event (e.g., cardiac data).

In an embodiment of the invention, stored data (either stored incircular buffer 1601, or priority queue 1603, or both) may be selectedin accordance with a retention policy in order to support intelligentdata loss (data triage) or offloading (e.g., to an external device) andto conserve memory usage and reduce/bound the time required to transferthe data. For example, an implanted device may store data in datastructure 1600 for sensor channels fulfilling a predetermined criteria,may discard waveform data while retaining statistics, summary data, orburden information, enable or disable or prioritize sensor channelsbased on algorithm criteria, sensor location, or sensor type, oroverride the retention policy when a clinician provides instructionsover a telemetry channel. Moreover, the embodiment may further use datacompression if the data is compressible to compress the data content ofthe new or old record.

Reporting Physiological Data

In accordance with another aspect of the invention, in response to aninstruction from a clinician, an implanted device organizes storedphysiological data according to the associated priority index andreports a predetermined number of data records that are deemed as havinga higher priority index than the other stored data records. Suchstructures for reporting stored physiological data are disclosed inFIGS. 12-14.

FIG. 17 shows flow diagram 1700 for reporting physiological data inaccordance with an embodiment of the invention. Step 1701 corresponds toan implanted device receiving a request (e.g., through a telemetrycommunications channel). In step 1703, the data records (both incircular buffer 1601 and priority queue 1603) are sorted according tothe associated priority index if the associated priority index issufficiently large (e.g., three or higher). Step 1705 determines if thenumber of reported data records is less than or equal to N. N can be,for example, the number of records that the user wishes to retrieve. Ifso, the physiological data associated with the data record is reportedto a clinician's workstation over the telemetry communications channeland the number of reported data is incremented in step 1707. Step 1705is then repeated. If the number of records is greater than N, thereporting of neurological data is terminated in step 1709, and procedure1700 is completed.

A physician may request physiological data associated with N datarecords that are stored in circular buffer 1601 and priority queue 1603and having a minimum priority index to be reported to, for example, aphysician programmer over a telemetry link. The physician programmer maythereby display the requested physiological data or at least those wherethe priority index is above a threshold. When so instructed, implanteddevice sorts the physiological data associated with the data records incircular buffer 1601 and priority queue 1603 and reports physiologicaldata associated with the N data records having at least the minimumpriority index. Once the data is reported, the implanted device mayrelease the memory space previously allocated to the identified datarecords, mark that memory space for deletion, and/or delete the datarecords. If more than N data records have the minimum priority index,the implanted device may select N data records based on a temporalcriterion (e.g., the most recent or the oldest), being greater than apredetermined priority index, or a priority index that is dependent onan external event. Moreover, system may select a data record so thateach occurring event type is included in the reported data records.Because the invention may be implanted within any implantable medicaldevice system, however, it will be appreciated that the externalcomponents may vary in configuration, components and/or features.

Data Format

FIG. 18 shows exemplary physiological data 1800 that can be retained inimplanted medical device. The physiological data 1800 comprises summaryinformation data 1801, pre-detection data 1803, post-detection data1805, and event/etc information data 1807. Pre-detection data 1803contains sampled data 1811, 1813, 1815, 1817, 1819, 1821, and 1823 thatis collected before a detected physiologic event such as an epilepticseizure. Post-detection data 1805 contains sampled data 1825, 1827,1829, 1831, 1833, 1835, 1837, and 1839 after the detected physiologicevent. In the exemplary data shown in FIG. 18, pre-detection data 1803includes sampled data 1809 and 1817 that are obtained from neurologicalchannel 1, sampled data 1811 and 1819 that are obtained fromneurological channel 2, sampled data 1813 and 1821 that are obtainedfrom neurological channel 3, and sampled ECG data 1815 and 1823 that areobtained from the ECG channel. Post-detection data 1805 includes sampleddata 1825 and 1833 that are obtained from neurological channel 1,sampled data 1827 and 1835 that are obtained from neurological channel2, sampled data 1829 and 1837 that are obtained from neurologicalchannel 3, and sampled data 1831 and 1839 that are obtained from the ECGchannel. While the physiologic channels sampled before and after thephysiologic event are same in exemplary record 1800, differentphysiologic channels may be sampled before and after the physiologicevent. Additionally, summary information data 1801 contains summaryinformation about record 1800. The embodiment of the invention supportsphysiological data that has a fixed length or that has a variablelength. Event/Etc information data 1807 includes information about theassociated physiologic event type and other associated information.Although depicted as data from different channels interleaved together,such data may also be stored in a non-interleaved fashion. For example,ECG may be stored separately from the other channels, etc.

FIG. 19 shows components of the exemplary physiological data as shown inFIG. 18. Summary information data 1801 includes trigger source data1901, length of event/etc information data 1903, size of loop record1905, and relevance information 1907. Trigger source data 1901identifies what triggered recording (e.g., a neurological channelnumber). Length of event/etc information data 1903 is indicative of thelength of event/etc data 1807, size of loop record 1905 contains thelength of record 1800, and relevance data 1907 indicates the relevancelevel of each sampled channel as will be later discussed. Event/Etcinformation 1807 contains entries 1909 and 1911. Each entry includesevent type 1913 that is indicative of an event associated with record1800, start offset data 1915 includes the offset of record 1800 from thestart of the loop recording, and type specific field 1917 includesspecific data that is associated with the event. (However, in anembodiment of the invention, a data entry may store a pointer tophysiologic data rather than store the physiologic data itself.) Record1800 may be associated with a plurality of event types, each beingindicated in separate entries, e.g., entries 1909 and 1911.

Data structure 1600 (as shown in FIG. 16) typically can store 1 to 16Mbytes of data. Record 1800 may contain anywhere from approximately 5Kbytes to approximately 1 Mbyte. Typically, a record contains 30-90Kbytes per record. The embodiment supports both fixed size records(e.g., 60 Kbytes) or variable size records. With variable size recordsthe retention scheme, as previously discussed, may require that aplurality of records or only portions of records be removed fromcircular buffer 201 in order to store a new record. Also, differentparts of a record may be stored in physically different memorycomponents (e.g., summary/header information data 601 in one place (alog) and sampled data 1803 and 1805 in another (waveform memory) with apointer in the header/summary information indicating where the start ofthe data is and how much data is there).

As discussed, in an embodiment of the invention, a data record may be apointer to physiologic data rather than store the physiologic dataitself. Thus, for example, summary information data 1801 and/orevent/etc information data 1807 may be stored in the first and seconddata structures wherein some or all of the entries may be mapped, viapointers, to more detailed and more space consuming waveform data(pre-detection data 1803, post-detection data 1805) in an associatedmemory (such as a loop record buffer).

Selective Storage of Data Channels

The embodiment supports the generation of records at different rates.The record rate will vary widely with an implanted device'sconfiguration and with the patient. For example, a clinician may desireto record every detected seizure over a time period. There are somepatients that have 1 seizure every 6 months, but there are some thathave 500 seizures a day. A typical patient may have 2 unique events(seizure, button press, etc) per day.

While FIG. 18 shows an exemplary configuration with three neurologicalchannels and an ECG channel, an embodiment of the invention supports avariable number of neurological channels so that the memory of animplanted device can store necessary information over a desired periodof time. The channels may be adjusted either in quasi-static manner orin a dynamic manner. In an embodiment, the implanted medical devicecontains a channel selection component, which may be software orhardware logic for performing a process of selecting the one or morechannels for data storage as described herein. An evaluation processingcomponent may thereby obtain the selected channel data and process thechannel data also in accordance with the techniques described herein.

For applications like the detection of epileptic seizures and thesubsequent recording of data, it is advantageous, from a quality andresource stand-point, to be able to select a subset (which may includeall physiologic channels) of the sensed input channels for detectionprocessing and/or loop-recording. While this can be done manually priorto the availability of relevant data by defining the selected channels,manual configuration is less flexible and less desirable than allowingthe closed-loop, real-time, quasi-real-time, periodic, or otherwiseautomated selection of physiologic channels.

With implantable detection algorithms and applications, there aretypically a multitude of input sense channels. The degree of interestfor each of these sense channels is often discernable while an implanteddevice is collecting data and storing the data in a memory component,e.g., a memory structure. As each sample is processed or stored as ashort recording of samples, an application specific method may beemployed to identify the most interesting (relevant) physiologicchannels. Samples from selected physiologic channels may be utilized.Detection processing is typically resource intensive such that allphysiologic channels may be utilized. Data recording in a loop-recordingrapidly fills memory and then later prologs telemetry. In order toeffectively process and store the samples, judicious selection ofphysiologic channels may be desired.

With a detection algorithm operating on physiological signals, it islikely that simply obtained information may reveal which channels toretain or continue processing. Often, physicians/users may be interestedin examining, using, and retaining data from the physiologic channels inwhich an indication of an event is present. For example, if a seizure isdetected on two of eight detection channels of data being recorded fromthe brain, only those two neurological channels need be retained. Inthis example, the savings in storage may be significant since only twochannels are kept and six neurological channels are discarded,corresponding to a 4 to 1 sample compression.

Sample compression may be important if memory of an implanted device islimited. In the above example, one needs to decide which two channelsshould be kept. The decision may be based upon a number of factorsincluding, independently-calculated channel severity (e.g., save themost severe), channel event onset time (e.g., save the first to detect),and seizure burden indication on the physiologic channel. In such ascenario, the flow diagram of FIG. 15 may be modified such that aseverity calculation is performed prior to actual storage of the data inthe first data structure. Or stored data records may be automaticallyremoved from those data channels that are determined that the data isnot important. Similarly, this approach may be extended to different andmixed physiologic signals. For example, if the multiple EEG channels arebeing polled, one may keep only those EEG channels where theneurological event data is most important (e.g., based on a severityscoring). If both cardiac, intra-cranial pressure (ICP) and EEG channelsare being polled, one may keep only the signal types that deviated fromnorm. If the intra-cranial pressure rises significantly, one may keepsamples from the ICP channel. If the previous scenario occurs whilethere is a tachycardia event, one may further keep samples from the ECGchannel. Furthermore, if a seizure occurs near the same time, one maykeep samples form all three channels.

The above approach may be extended to include the retention of more thanone channel from a channel list sorted by relevancy as determined by afunction of various factors (e.g., onset time, presence and severity ofan event) as previously discussed. One may keep the most relevantphysiologic channels of the channel list. For example, one may keep thethree most relevant (“interesting”) physiologic channels of fivephysiologic channels. Keeping the two or most relevant physiologicchannels is referred as the “multi-max” of the channel list.

Alternatively, the system may retain a composite signal, which may be,for example, the sum of a plurality of channels. Other embodiments ofthe invention may utilize other derivatives. Furthermore, the channelsthemselves may be down-sampled or precision-reduced so that, forexample, the least relevant samples are kept at 16 times less precisionin amplitude and 2 times lower sampling rate resulting in about 4 timessmaller data size.

Furthermore, with seizure detection and many other neurologicalapplications the most interesting physiologic channels may be identifiedas those physiologic channels that are associated with the maximumenergy value, normalized energy value, severity, or energy approximatedvalue in the applications seizure frequency domain. For seizuredetection, the seizure frequency domain may be 5-70 Hz (more narrowlythis is typically 5-45 Hz) or (for fast ripple detections) at very highfrequency (approximately 200 Hz or more). The energy value may often besampled as the “rectified” (absolute value, square, etc.) of the samplestaken directly from the filtered EEG signal. While this data mayconstantly be higher in some neurological locations, it is useful tonormalize the data across the physiologic channels with manual orautomatic gain control. Automatic gain control may be implemented as thedaily comparison of running 1-pole filters and with the appropriateadjustment in response or in some other manner. For example, the gain ofeach physiologic channel may be adjusted so that the associatedbackground signals are similar (to each other and/or to a target value),which may be referred to as background normalization. Because shortsignals may appear similar to interesting material over the short term,it is useful to smooth or reject outliers from the energy signals beforecomparison. Smoothing may be done, for example, using 1-pole filters,voting schemes, running or block percentile filters, percentile trackingtechnologies or slew-rate limiters to eliminate or mitigate, forexample, the effect of epileptiform discharges (ED's) andsleep-spindles.

The embodiment supports different criteria for selecting channels forretention from a set of N physiologic channels. Different selectioncriteria include Max, MultiMax, MaxDeviationRetention, andTime-Distributed Max, MultiMax or MaxDeviation criterion. With the Maxcriterion, the physiologic channel with the highest energy is selected.With the MultiMax criterion, the M of N physiologic channels with thehighest energy signals are selected. The selection may be implemented ina number of approaches, including multiple passes and sortingtechniques. With the MaxDeviationRetention criterion, the physiologicchannel with the highest energy is selected (as with the Max criterion).Moreover, P additional physiologic channels are selected that have anenergy value greater than a determined fraction of the highest energyvalue. Variations of the above three criteria (Max, MultiMax, andMaxDeviation) may formed by selecting instantaneous values or byprocessing the physiologic channels with a window function. Whendetermining a processed value, a physiologic channel maybe selectedbased on a configurable long to very short-term running window. Thewindow may be based on any number of criteria including withoutlimitation one or more of the following: median (or other percentile) ofthe window; mean of the window; running 1-pole value (e.g., one for eachphysiologic channel in which an associated time constant defines thewidth of an “effective” window); and accumulated absolute differencessum/accumulation (i.e., line-length). The accumulated differencecriterion accumulates the difference of all channels with respect to aselected zero-channel. If there are accumulations greater than zero, thelargest of those physiologic channels is selected.

With an embodiment of the invention, the selection of physiologicchannels may occur after filtering (e.g., bandpass, notch, FIR, and IIR)the physiologic channels. For example, an EEG signal may be filtered inthe 10-60 Hz range to remove the bulk of the EEG energy content that mayotherwise mask the ictal content. As another example, the physiologicchannels may be filtered in the 180-250 Hz range in order to study“fast-ripple” events.

The above channel selection process is applicable both for recordsstored in circular buffer 1601 and priority queue 1603. Moreover, thechannel selection criterion for circular buffer 1601 may be differentfrom the channel selection criterion for priority queue 1603.

In an embodiment of the invention, a “channel compositing” process issupported. A physiologic data sample is obtained from each of a subsetof physiologic channels at an approximate time instance. For example, animplanted device may interface with N physiologic channels. A firstsubset of physiologic channels may include the first N/2 physiologicchannels, a second subset may include the next N/2−1 physiologicchannels, and a third subset may include the last physiologic channel.(A subset of physiologic channels may include all physiologic channels,one physiologic channel, or some number of physiologic channels inbetween.) Physiologic channels may be grouped into subsets in accordancedifferent criterion, including the proximity of electrodes and theassociated physiological functionality. A composite data may bedetermined from the sampled data of each subset of physiological dataand stored in a data record. For example, the composite data may be themedian value of the sampled data for the associated subset ofphysiologic channels. The embodiment may determine the composite data byother ways. For example, the minimum value, the maximum value, or thevariation among the associated physiologic channels may be used. Also,the composite data may include a mixture of a plurality of physiologicdata samples in a subset, e.g., a sum of selected physiologic datasamples or a ratio of the largest physiologic data sample to thesmallest physiologic data sample. Composite data is stored in a datarecord for each subset of physiologic channels.

FIG. 20 shows the selection of channel data for retention in datastructure 1600. In the embodiment, channel selection component 2001 anddata structure 1600 are supported by an implanted component. Channelselection component 2001 obtains N physiologic channels from varioussensors that may include neurological signals, EEG signals, and amixture of physiologic signals. Channel selection component 2001 selectsa subset of physiologic channels from the N physiologic channels using aselection criterion as previously discussed. Data from the selectedphysiologic channels is included in record 1800. Moreover, the selectedphysiologic channels may be processed by the implanted device and/orstored into memory. The embodiment, as shown in FIG. 20, stores record1800 into data structure 1600 as previously discussed. Similarly, theabove approach may be extended to different and mixed physiologicalsignals.

In the embodiment, channel selection component 2001 includes a channelprocessor that selects a subset of physiological channels using theselection criterion. The channel processor may be implemented with amicroprocessor, a signal processor, or other processor means.

As can be appreciated by one skilled in the art, a computer system withan associated computer-readable medium containing instructions forcontrolling the computer system can be utilized to implement theexemplary embodiments that are disclosed herein. The computer system mayinclude at least one computer such as a microprocessor, digital signalprocessor, and associated peripheral electronic circuitry.

Thus, embodiments of the invention are disclosed. One skilled in the artwill appreciate that the above teachings can be practiced withembodiments other than those disclosed. The disclosed embodiments arepresented for purposes of illustration and not limitation, and theinventions are limited only by the claims that follow.

1. A method for processing physiologic data from a plurality ofphysiologic input sense channels monitored by a medical device, themethod comprising: (A) determining by a processor a selection criterionfor selecting from the plurality of physiologic channels; (B)dynamically selecting by a processor a first input sense channel subsetof physiologic input sense channels from the plurality of physiologicinput sense channels based on the selection criterion at a first timevalue; (C) retaining a first data sensed through the dynamicallyselected first input sense channel subset of physiologic input sensechannels; (D) dynamically selecting by the processor a second inputsense channel subset of physiologic input sense channels from theplurality of physiologic input sense channels based on the selectioncriterion at a second time value; (E) retaining a second data sensedthrough the dynamically selected second input sense channel subset ofphysiologic input sense channels; and (F) combining by the processor atleast two of the selected input sense channel subsets of physiologicinput sense channels into a composite channel, the combining based on aselection criterion associated with a characteristic of at least one ofthe plurality of physiologic input sense channels.
 2. The method ofclaim 1, wherein (C) comprises storing the first data in a first datarecord and wherein (E) comprises storing the second data in a seconddata record.
 3. The method of claim 1, wherein (B) comprises: (i)sorting the plurality of physiologic input sense channels by relevancy;and (ii) selecting those physiologic input sense channels that have ahighest relevancy.
 4. The method of claim 3, wherein the relevancy isassociated with a function, and wherein factors of the function areselected from the group consisting of an onset time, presence of aphysiologic event, and a severity of the physiologic event.
 5. Themethod of claim 1, wherein the first input sense channel subsetcomprises a first physiologic input sense channel from the plurality ofphysiologic input sense channels, and wherein the first physiologicinput sense channel corresponds to a highest energy for the plurality ofphysiologic input sense channels.
 6. The method claim 5, wherein thefirst input sense channel subset comprises another physiologic inputsense channel from the plurality of physiologic input sense channels,and wherein the other physiologic input sense channel corresponds to anext highest energy.
 7. The method of claim 5, wherein the first inputsense channel subset comprises another physiologic input sense channelfrom the plurality of physiologic input sense channels, and wherein theother physiologic input sense channel corresponds to a predeterminedfraction of the highest energy.
 8. The method of claim 1, furthercomprising: (F) processing each physiologic input sense channel of theplurality of physiologic input sense channels with a window function. 9.The method of claim 8, wherein the first input sense channel subsetcomprises a first physiologic input sense channel from the plurality ofphysiologic input sense channels, and wherein the first physiologicinput sense channel corresponds to a highest energy for the plurality ofphysiologic input sense channels.
 10. The method of claim 9, wherein thefirst input sense channel subset comprises another physiologic inputsense channel from the plurality of physiologic input sense channels,and wherein the other physiologic input sense channel corresponds to anext highest energy.
 11. The method of claim 1, wherein the first inputsense channel subset equals the second input sense channel subset. 12.The method of claim 1, wherein (C) comprises storing the first data in afirst data record and wherein (E) comprises storing the second data inthe first data record.
 13. The method of claim 12, wherein the firstdata comprises a composite data and further comprising: (F) determiningthe composite data from sampled data for the first input sense channelsubset of physiologic input sense channels.
 14. The method of claim 13,wherein (F) comprises: (i) determining a median value for the firstinput sense channel subset of physiologic input sense channels at anapproximate time instance.
 15. The method of claim 1, wherein thecomposite channel is the sum of a plurality of channels.
 16. A medicaldevice for processing physiologic data from a plurality of physiologicinput sense channels, comprising: (A) a physiologic sensing componentthat obtains the physiologic data from the plurality of physiologicinput sense channels; (B) a channel selection component that selects aninput sense channel subset of physiologic input sense channels from theplurality of physiologic input sense channels based on a selectioncriterion for storage, the channel selection component configured tocombine at least two of the selected input sense channel subsets ofphysiologic input sense channels into a composite channel based on theselection criterion, wherein the selection is associated with acharacteristic of at least one of the plurality of physiologic channels;and (C) a memory component that stores channel data corresponding to theselected channel subset of physiologic input sense channels.
 17. Themedical device of claim 16, further comprising: (D) an evaluationprocessor that obtains channel data from the input sense channelselection component and processes the channel data for storage in thememory component based on the selection of the input sense channelsubset.
 18. The medical device of claim 17, wherein the processorutilizes the channel data for treatment associated with a physiologicevent.
 19. The medical device of claim 16, wherein the channel selectioncomponent comprises a channel processor, and wherein the channelprocessor is configured to perform: (i) selecting the input sensechannel subset of physiologic input sense channels from the plurality ofphysiologic input sense channels based on the selection criterion at atime value; (ii) retaining a first data associated with the channelsubset of physiologic input sense channels; (iii) selecting anotherinput sense channel subset of physiologic input sense channels from theplurality of physiologic input sense channels based on the selectioncriterion at another time value; and (iv) retaining a second dataassociated with the other input sense channel subset of physiologicinput sense channels.
 20. The medical device of claim 16, wherein thecomposite channel is the sum of a plurality of channels.
 21. A methodfor processing physiologic data from a plurality of physiologic inputsense channels monitored by an implantable medical device, the methodcomprising: (A) monitoring a set of physiological signals sensed over aplurality of physiologic input sense channels; (B) dynamically selectingby a processor a input sense channel subset from the plurality of inputsense physiologic channels based on detection of a neurological event;and (C) retaining only data sensed via the dynamically selected inputsense channel subset with respect to the plurality of input sensephysiologic channels in memory of the implantable medical device.
 22. Animplantable medical device for processing physiologic data from aplurality of physiologic input sense channels, comprising: (A) aphysiologic sensing component that monitors the physiologic data sensedover the plurality of physiologic input sense channels; (B) a channelselection component that dynamically selects an input sense channelsubset from the plurality of physiologic input sense channels based ondetection of a neurological event; and (C) a memory component thatstores only data sensed via the dynamically selected input sense channelsubsets with respect to the plurality of input sense physiologicchannels.